The comparison of geometric and electronic properties of molecular surfaces by neural networks: Application to the analysis of corticosteroid-binding globulin activity of steroids. - Soheila Anzali; Gerhard Barnickel; Michael Krug; Jens Sadowski; Markus Wagener; Johann Gasteiger; Jaroslaw Polanski (J. Comput. Aided Mol. Des., 1996)

Neural Nets for the Simulation of Molecular Recognition within MS-Windows Environment. - Jaroslaw Polanski (J. Chem. Inf. Comput. Sci., 1996)

The Receptor-like Neural Network for Modeling Corticosteroid and Testosterone Binding Globulins. - Jaroslaw Polanski (J. Chem. Inf. Comput. Sci., 1997)

The Comparative Molecular Surface Analysis (COMSA): A Novel Tool for Molecular Design. - Jaroslaw Polanski; Beata Walczak (Comput. Chem., 2000)

The Comparative Molecular Surface Analysis (COMSA) - A Nongrid 3D QSAR Method by a Coupled Neural Network and PLS System: Predicting pKa Values of Benzoic and Alkanoic Acids. - Jaroslaw Polanski; Rafal Gieleciak; Andrzej Bak (J. Chem. Inf. Comput. Sci., 2002)

Modeling Steric and Electronic Effects in 3D- and 4D-QSAR Schemes: Predicting Benzoic pKa Values and Steroid CBG Binding Affinities. - Jaroslaw Polanski; Andrzej Bak (J. Chem. Inf. Comput. Sci., 2003)

The Comparative Molecular Surface Analysis (CoMSA) with Modified Uniformative Variable Elimination-PLS (UVE-PLS) Method: Application to the Steroids Binding the Aromatase Enzyme. - Jaroslaw Polanski; Rafal Gieleciak (J. Chem. Inf. Comput. Sci., 2003)

Comparative Molecular Surface Analysis (CoMSA) for Modeling Dye-Fiber Affinities of the Azo and Anthraquinone Dyes. - Jaroslaw Polanski; Rafal Gieleciak; Miroslaw Wyszomirski (J. Chem. Inf. Comput. Sci., 2003)

GRID Formalism for the Comparative Molecular Surface Analysis: Application to the CoMFA Benchmark Steroids, Azo Dyes, and HEPT Derivatives. - Jaroslaw Polanski; Rafal Gieleciak; Tomasz Magdziarz; Andrzej Bak (J. Chem. Inf. Model., 2004)

Modeling Robust QSAR. 1. Coding Molecules in 3D-QSAR - from a Point to Surface Sectors and Molecular Volumes. - Rafal Gieleciak; Tomasz Magdziarz; Andrzej Bak; Jaroslaw Polanski (J. Chem. Inf. Model., 2005)

Modeling Robust QSAR. - Jaroslaw Polanski; Andrzej Bak; Rafal Gieleciak; Tomasz Magdziarz (J. Chem. Inf. Model., 2006)

Modeling Robust QSAR 3: SOM-4D-QSAR with Iterative Variable Elimination IVE-PLS: Application to Steroid, Azo Dye, and Benzoic Acid Series. - Andrzej Bak; Jaroslaw Polanski (J. Chem. Inf. Model., 2007)

Modeling Robust QSAR, 2. Iterative Variable Elimination Schemes for CoMSA: Application for Modeling Benzoic Acid pKa Values. - Rafal Gieleciak; Jaroslaw Polanski (J. Chem. Inf. Model., 2007)

No free lunches in nature? An analysis of the regional distribution of the affiliations of Nature publications. - Jacek Bogocz; Andrzej Bak; Jaroslaw Polanski (Scientometrics, 2014)

Ligand-Based Virtual Screening in a Search for Novel Anti-HIV-1 Chemotypes. - Agata Kurczyk; Dawid Warszycki; Robert Musiol; Rafal Kafel; Andrzej J. Bojarski; Jaroslaw Polanski (J. Chem. Inf. Model., 2015)

The analysis of the market success of FDA approvals by probing top 100 bestselling drugs. - Jaroslaw Polanski; Jacek Bogocz; Aleksandra Tkocz (J. Comput. Aided Mol. Des., 2016)

Beware of ligand efficiency (LE): understanding LE data in modeling structure-activity and structure-economy relationships. - Jaroslaw Polanski; Aleksandra Tkocz; Urszula Kucia (J. Cheminformatics, 2017)

Between Descriptors and Properties: Understanding the Ligand Efficiency Trends for G Protein-Coupled Receptor and Kinase Structure-Activity Data Sets. - Jaroslaw Polanski; Aleksandra Tkocz (J. Chem. Inf. Model., 2017)

Chemoinformatics: From Chemical Art to Chemistry in Silico. - Jaroslaw Polanski (Encyclopedia of Bioinformatics and Computational Biology (2), 2019)